Self-regulated learning in ai-supported language learning: A self-determination theory perspective on critical thinking, teacher support, and flow
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Metacognitive and self-regulatory processes play an important role in enabling students to resist cognitive tendencies and engage in deliberate evaluation.
“From a learning perspective, metacognitive and self-regulatory processes play an important role in enabling students to resist these cognitive tendencies and engage in deliberate evaluation (Liu, 2026;Zhao & Jin, 2026).”
From Think Before You Accept: Can Written Justification Reduce Uncritical Uptake of AI Writing Suggestions? (2026) · cites this paper as Zhao & Jin, 2026
Cites
Evaluating structural equation models with unobservable variables and measurement error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.1177/002224378101800104 · Cited by 109,190 · see citing works
The "what" and "why" of goal pursuits: Human needs and the self-determination of behavior
Deci, E. L., & Ryan, R. M. (2000) · Psychological Inquiry · doi:10.1207/s15327965pli1104_01 · Cited by 34,210 · see citing works
Grounded theory research: Procedures, canons, and evaluative criteria
Corbin, J. M., & Strauss, A. (1990) · Qualitative Sociology · doi:10.1007/bf00988593 · Cited by 11,133 · see citing works
Niemiec, C. P., & Ryan, R. M. (2009) · Theory and Research in Education · doi:10.1177/1477878509104318 · Cited by 2,542 · see citing works
The development and psychometric validation of a Critical Thinking Disposition Scale
Sosu, E. M. (2013) · Thinking Skills and Creativity · doi:10.1016/j.tsc.2012.09.002 · Cited by 324 · see citing works
Foreign language acquisition via artificial intelligence and extended reality: design and evaluation
Divekar, R. R., Drozdal, J., Chabot, S. R. V., Zhou, Y., Su, H., Chen, Y., Zhu, H., Hendler, J., & Braasch, J. (2021) · Computer Assisted Language Learning · doi:10.1080/09588221.2021.1879162 · Cited by 284 · see citing works
Yang, H., & Kyun, S. (2022) · Australasian Journal of Educational Technology · doi:10.14742/ajet.7492 · Cited by 208 · see citing works
Wang, X., & Reynolds, B. L. (2024) · Education Sciences · doi:10.3390/educsci14050496 · Cited by 198 · see citing works
Wang, X., & Wang, S. (2024) · Learning and Motivation · doi:10.1016/j.lmot.2024.102014 · Cited by 181 · see citing works
Wu, H., & Wang, Y. (2025) · Learning and Motivation · doi:10.1016/j.lmot.2025.102134 · Cited by 149 · see citing works
Hong, J., Hwang, M., Tai, K., & Lin, P. (2017) · Computer Assisted Language Learning · doi:10.1080/09588221.2017.1329215 · Cited by 146 · see citing works
Pack, A., & Maloney, J. S. (2023) · TESOL Quarterly · doi:10.1002/tesq.3253 · Cited by 140 · see citing works
Unravelling students’ perceived EFL teacher support
Liu, H., & Li, X. (2023) · System · doi:10.1016/j.system.2023.103048 · Cited by 130 · see citing works
Wang, Y., & Guo, Y. (2026) · Journal of Computer Assisted Learning · doi:10.1002/jcal.70189 · Cited by 111 · see citing works
Schuitema, J. A., Peetsma, T. T. D., & van der Veen, I. (2016) · Learning and Individual Differences · doi:10.1016/j.lindif.2016.05.006 · Cited by 100 · see citing works
Khoso, A. K., Hong-gang, W., & Darazi, M. A. (2025) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2025.100627 · Cited by 78 · see citing works
Student Flow and Burnout: The Role of Teacher Autonomy Support and Student Autonomous Motivation
Golub, T. L., Rijavec, M., & Olčar, D. (2020) · Psychological Studies · doi:10.1007/s12646-019-00539-6 · Cited by 61 · see citing works
Sun, F., Mendoza, L., Wang, J., & Li, H. (2025) · Behavioral Sciences · doi:10.3390/bs15070983 · Cited by 61 · see citing works
Joo, Y. J., Joung, S., & Kim, J. (2012) · Interactive Learning Environments · doi:10.1080/10494820.2012.745421 · Cited by 56 · see citing works
Ma, M. (2024) · International Journal of Applied Linguistics · doi:10.1111/ijal.12603 · Cited by 55 · see citing works
Liu, H., & Fan, J. (2026) · Language learning & technology · doi:10.64152/10125/73684 · Cited by 47 · see citing works
Sun, F., Wang, J., Mendoza, L., & Li, H. (2026) · Acta Psychologica · doi:10.1016/j.actpsy.2026.106237 · Cited by 46 · see citing works
Kumar, T., Soozandehfar, S. M. A., Hashemifardnia, A., & Mombeini, R. (2023) · Language Testing in Asia · doi:10.1186/s40468-023-00251-3 · Cited by 42 · see citing works
L2 Students' Speaking Skills in Robot‐Assisted Language Learning: A Meta‐Analysis
Wang, Y., Pan, Z., & Solhi, M. (2025) · European Journal of Education · doi:10.1111/ejed.70416 · Cited by 42 · see citing works
Wan, K., King, V., & Chan, K. (2021) · The Electronic Journal of e-Learning · doi:10.34190/ejel.19.6.2117 · Cited by 35 · see citing works
Wang, Y., & Yan, X. (2025) · Learning and Individual Differences · doi:10.1016/j.lindif.2025.102788 · Cited by 33 · see citing works
Wang, Y., & Wang, S. (2026) · Innovation in Language Learning and Teaching · doi:10.1080/17501229.2026.2683871 · Cited by 32 · see citing works
Zhang, J., & Liu, W. (2026) · Innovation in Language Learning and Teaching · doi:10.1080/17501229.2026.2682435 · Cited by 25 · see citing works
Chen, H., Yohannes, A., & Hung, N. (2024) · British Journal of Educational Technology · doi:10.1111/bjet.13519 · Cited by 20 · see citing works
Wang, Y., Li, H., & Savaş, H. (2025) · Journal of Education for Students Placed at Risk (JESPAR) · doi:10.1080/10824669.2025.2599161 · Cited by 19 · see citing works
张, 杰., Zhou, X., & Yingsoon, G. Y. (2025) · Acta Psychologica · doi:10.1016/j.actpsy.2025.105703 · Cited by 12 · see citing works
Examining the Flow Dynamics of Artificial Intelligence in Real-Time Classroom Applications
Szűts, Z., Molnar, T., Racsko, R., Vaughan, G., Ceglédi, S., & Dominek, D. L. (2025) · Computers · doi:10.3390/computers14070275 · Cited by 9 · see citing works
Lee, S., Lee, Y., Park, S., & Ham, E. H. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13443-6 · Cited by 8 · see citing works
Kong, S. C., Lin, T. J., & Yee Man Kayla, S. I. U. (2025) · Computers & Education · doi:10.1016/j.compedu.2025.105249 · Cited by 7 · see citing works
Li, L. L., Mao, G., Zhang, L., & Ying, J. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13849-2 · Cited by 4 · see citing works
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Tao, Y., Meyer, J., & Kizilcec, R. F. (2026) · arXiv · doi:10.48550/arxiv.2609.23936
Huang, Y., & Shi, L. (2026) · Learning and Motivation · doi:10.1016/j.lmot.2026.102325
Xu, J., & Ren, M. (2026) · Learning and Motivation · doi:10.1016/j.lmot.2026.102365
Li, J., & Li, P. C. (2026) · Learning and Motivation · doi:10.1016/j.lmot.2026.102370
Jingye, L., Halim, H. A., & Saad, M. R. B. M. (2026) · Learning and Motivation · doi:10.1016/j.lmot.2026.102376
- Authors
- Zhao, Y., & Jin, H.
- Affiliations
- Macao Polytechnic University (MO)
- Corresponding author
- Jin, Huiyi
- ORCID
- Jin, Huiyi
- Venue
- Learning and Motivation
- Publisher
- Elsevier BV
- Published
- 2026-08
- Volume
- 95
- Pages
- 102299
- ISSN
- 0023-9690 (ISSN-L)
- OpenAlex
- W7165453461
- Cited by
- 4
- References
- 35
- Citations by year
- 2026: 4
- FWCI
- 80.41
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Learning and Motivation (publishedVersion)
- Topics
- Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Keywords
- student self-regulation, AI-assisted language learning, self-determination theory, critical thinking disposition, teacher support, flow, learner autonomy, mediation, undergraduate students
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